1. Field
The present disclosure relates to a stereoscopic image generation method, a system using the same, and a recording medium for the same, and, more particularly, to a stereoscopic image generation method of background terrain scenes, a system using the same, and a recording medium for the same.
2. Description of the Related Art
With the development of the three-dimensional (3D) display technology, demand for stereoscopic 3D images is rapidly increasing. Many of the recently released movies have been produced in 3D stereo. The stereo effects provide the audience with vivid realism by assigning different depths to layers of differing distances.
In a typical move, a variety of background sceneries are captured from the sky using an airplane or a helicopter. It is extremely difficult, however, to shoot such scenes with a stereo camera rig in an airplane or a helicopter. A successful stereo reconstruction requires correct calibration of the cameras. This calibration is very sensitive and, in an environment such as a helicopter, the vibrations of the engine can easily misalign the cameras. A better alternative is to shoot background terrain scenes with a single camera and to convert them into 3D.
There are two different approaches in conversion from two-dimensional (2D) image to 3D image. One is fully image based approach and the other is geometry based approach. In general, for 2D to 3D conversion of terrain scenes, geometry based approach is better than image based approach. The image based approach is not suitable for compositing objects other than terrain and is hard to modify depth information. One of the key advantages of the geometry based approach is that the time coherence is easily enforced and it gives accurate data for inter-object depth using terrain geometry.
Although there have been several previous approaches on creating terrain geometry using images, they were majorly concerned on applying the geometry for compositing objects. Accordingly, such methods aim to recreate a smooth surface where virtual characters could be placed and somehow disregard smaller errors in benefit of smoothness and manageable geometry. However, smaller imperfections in the geometry have influence on the creation of virtual images, which could lead to visual fatigue if such imperfections persist the length of the film. Thus, there is a need for solving the problem of refining the estimated geometry in order to minimize the errors.
Depth information can be divided into two types, which are inter-object depth and inner-object depth. The inter-object depth is the relative depth between two objects in the scene and it is important especially at the boundaries of the objects since an error in the inter-object depth will produce remarkable visual artifacts. The inner-object depth means the depth variation within a single object region. Many 2D to 3D conversion algorithms recover the inter-object depth but disregard the inner-object depth resulting often in the so-called card board effect. Manual recovery of inter-object depth can be easily achieved by rotoscoping the scene objects and it has become a usual practice in 2D to 3D conversion. In contrast, it is hard to get the accurate inner-object depth. In large terrain scenes, the terrain often varies smoothly, thus, in order to recover the geometry, the inner-object depth is mainly used.